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PLoS One ; 14(11): e0225271, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31747438

RESUMO

Understanding the entirety of basin-scale C cycling (DOC fluxes and CO2 exchanges) are central to a holistic perspective of boreal forest biogeochemistry today. Shifts in the timing and magnitude of dissolved organic carbon (DOC) delivery in streams and eventually into oceans can be expected, while simultaneously CO2 emission may exceed CO2 fixation, leading to forests becoming stronger CO2 sources than sinks amplifying rising trace gases in the atmosphere. At May Creek, a representative late-successional boreal forest watershed at the headwaters of the Copper River Basin, Alaska, we quantified the seasonality of DOC flux and landscape-scale CO2 exchange (eddy covariance) over two seasonal cycles. We deployed in situ fDOM and conductivity sensors, performed campaign sampling for water quality (DOC and water isotopes), and used fluorescence spectroscopy to ascertain DOC character. Simultaneously, we quantified net CO2 exchange using a 100 ft eddy covariance tower. Results indicate DOC exports were pulse-driven and mediated by precipitation events. Both frequency and magnitude of pulse-driven DOC events diminished as the seasonal thaw depth deepened, with inputs from terrestrial sources becoming major contributors to the DOC pool with decreasing snowmelt contribution to the hydrograph. A three-component parallel factorial analysis (PARAFAC) model indicated DOC liberated in late-season may be bioavailable (tyrosine-like). Combining Net Ecosystem Exchange (NEE) measurements indicate that the May Creek watershed fixes 142-220 g C m-2 yr-1 and only 0.40-0.57 g C m-2 yr-1 is leached out as DOC. Thus, the May Creek watershed and similar mature spruce forest dominated watersheds in the Copper River Basin are currently large ecosystem C sinks and exceeding C conservative. An understanding of DOC fluxes from Gulf of Alaska watersheds is important for characterizing future climate change-induced seasonal shifts.


Assuntos
Ciclo do Carbono , Alaska , Simulação por Computador , Florestas , Rios , Estações do Ano , Tempo (Meteorologia)
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